Merge changes from github.

Change: 131310818

configure

@@ -80,6 +80,7 @@ while [ "$TF_NEED_CUDA" == "" ]; do
   esac
 done
 
+export TF_NEED_CUDA
 if [ "$TF_NEED_CUDA" == "0" ]; then
   echo "Configuration finished"
   exit
@@ -97,6 +98,7 @@ while true; do
     fi
   fi
   if [ -e "$GCC_HOST_COMPILER_PATH" ]; then
+    export CC=$GCC_HOST_COMPILER_PATH
     break
   fi
   echo "Invalid gcc path. ${GCC_HOST_COMPILER_PATH} cannot be found" 1>&2
@@ -107,7 +109,6 @@ while true; do
   # Retry
 done
 
-
 # Find out where the CUDA toolkit is installed
 OSNAME=`uname -s`
 
@@ -140,6 +141,8 @@ while true; do
   fi
 
   if [ -e "${CUDA_TOOLKIT_PATH}/${CUDA_RT_LIB_PATH}" ]; then
+    export CUDA_TOOLKIT_PATH
+    export CUDA_VERSION=$TF_CUDA_VERSION
     break
   fi
   echo "Invalid path to CUDA $TF_CUDA_VERSION toolkit. ${CUDA_TOOLKIT_PATH}/${CUDA_RT_LIB_PATH} cannot be found"
@@ -200,13 +203,16 @@ while true; do
   fi
 
   if [ -e "$CUDNN_INSTALL_PATH/${CUDA_DNN_LIB_ALT_PATH}" -o -e "$CUDNN_INSTALL_PATH/${CUDA_DNN_LIB_PATH}" ]; then
+    export CUDNN_VERSION=$TF_CUDNN_VERSION
+    export CUDNN_INSTALL_PATH
     break
   fi
 
   if [ "$OSNAME" == "Linux" ]; then
     CUDNN_PATH_FROM_LDCONFIG="$(ldconfig -p | sed -n 's/.*libcudnn.so .* => \(.*\)/\1/p')"
     if [ -e "${CUDNN_PATH_FROM_LDCONFIG}${TF_CUDNN_EXT}" ]; then
-      CUDNN_INSTALL_PATH="$(dirname ${CUDNN_PATH_FROM_LDCONFIG})"
+      export CUDNN_VERSION=$TF_CUDNN_VERSION
+      export CUDNN_INSTALL_PATH="$(dirname ${CUDNN_PATH_FROM_LDCONFIG})"
       break
     fi
   fi
@@ -225,42 +231,11 @@ while true; do
   CUDNN_INSTALL_PATH=""
 done
 
-cat > third_party/gpus/cuda/cuda.config <<EOF
-# CUDA_TOOLKIT_PATH refers to the CUDA toolkit.
-CUDA_TOOLKIT_PATH="$CUDA_TOOLKIT_PATH"
-# CUDNN_INSTALL_PATH refers to the cuDNN toolkit. The cuDNN header and library
-# files can be either in this directory, or under include/ and lib64/
-# directories separately.
-CUDNN_INSTALL_PATH="$CUDNN_INSTALL_PATH"
-
-# The Cuda SDK version that should be used in this build (empty to use libcudart.so symlink)
-TF_CUDA_VERSION=$TF_CUDA_VERSION
-
-# The Cudnn version that should be used in this build
-TF_CUDNN_VERSION=$TF_CUDNN_VERSION
-EOF
-
-# Configure the gcc host compiler to use
-export WARNING=$DO_NOT_SUBMIT_WARNING
-perl -pi -e "s,CPU_COMPILER = \('.*'\),# \$ENV{WARNING}\nCPU_COMPILER = ('$GCC_HOST_COMPILER_PATH'),s" third_party/gpus/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc
-perl -pi -e "s,GCC_HOST_COMPILER_PATH = \('.*'\),# \$ENV{WARNING}\nGCC_HOST_COMPILER_PATH = ('$GCC_HOST_COMPILER_PATH'),s" third_party/gpus/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc
-
-# Configure the platform name.
-perl -pi -e "s,PLATFORM = \".*\",PLATFORM = \"$OSNAME\",s" third_party/gpus/cuda/platform.bzl
-
-# Configure the Cuda toolkit version to work with.
-perl -pi -e "s,(GetCudaVersion.*return )\"[0-9\.]*\",\1\"$TF_CUDA_VERSION\",s" tensorflow/stream_executor/dso_loader.cc
-perl -pi -e "s,CUDA_VERSION = \"[0-9\.]*\",CUDA_VERSION = \"$TF_CUDA_VERSION\",s" third_party/gpus/cuda/platform.bzl
-
-# Configure the Cudnn version to work with.
-perl -pi -e "s,(GetCudnnVersion.*return )\"[0-9\.]*\",\1\"$TF_CUDNN_VERSION\",s" tensorflow/stream_executor/dso_loader.cc
-perl -pi -e "s,CUDNN_VERSION = \"[0-9\.]*\",CUDNN_VERSION = \"$TF_CUDNN_VERSION\",s" third_party/gpus/cuda/platform.bzl
-
-
 # Configure the compute capabilities that TensorFlow builds for.
 # Since Cuda toolkit is not backward-compatible, this is not guaranteed to work.
 while true; do
   fromuser=""
+  default_cuda_compute_capabilities="3.5,5.2"
   if [ -z "$TF_CUDA_COMPUTE_CAPABILITIES" ]; then
 cat << EOF
 Please specify a list of comma-separated Cuda compute capabilities you want to build with.
@@ -270,6 +245,9 @@ EOF
     read -p "[Default is: \"3.5,5.2\"]: " TF_CUDA_COMPUTE_CAPABILITIES
     fromuser=1
   fi
+  if [ -z "$TF_CUDA_COMPUTE_CAPABILITIES" ]; then
+    TF_CUDA_COMPUTE_CAPABILITIES=$default_cuda_compute_capabilities
+  fi
   # Check whether all capabilities from the input is valid
   COMPUTE_CAPABILITIES=${TF_CUDA_COMPUTE_CAPABILITIES//,/ }
   ALL_VALID=1
@@ -285,34 +263,13 @@ EOF
       exit 1
     fi
   else
+    export CUDA_COMPUTE_CAPABILITIES=$TF_CUDA_COMPUTE_CAPABILITIES
     break
   fi
   TF_CUDA_COMPUTE_CAPABILITIES=""
 done
 
-if [ ! -z "$TF_CUDA_COMPUTE_CAPABILITIES" ]; then
-  export WARNING=$DO_NOT_SUBMIT_WARNING
-  function CudaGenCodeOpts() {
-    OUTPUT=""
-    for CAPABILITY in $@; do
-      OUTPUT=${OUTPUT}"   \"${CAPABILITY}\",     "
-    done
-    echo $OUTPUT
-  }
-  export CUDA_GEN_CODES_OPTS=$(CudaGenCodeOpts ${TF_CUDA_COMPUTE_CAPABILITIES//,/ })
-  perl -pi -0 -e 's,\n( *)([^\n]*supported_cuda_compute_capabilities\s*=\s*\[).*?(\]),\n\1# $ENV{WARNING}\n\1\2$ENV{CUDA_GEN_CODES_OPTS}\3,s' third_party/gpus/crosstool/clang/bin/crosstool_wrapper_driver_is_not_gcc
-  function CudaVersionOpts() {
-    OUTPUT=""
-    for CAPABILITY in $@; do
-      OUTPUT=$OUTPUT"CudaVersion(\"${CAPABILITY}\"), "
-    done
-    echo $OUTPUT
-  }
-  export CUDA_VERSION_OPTS=$(CudaVersionOpts ${TF_CUDA_COMPUTE_CAPABILITIES//,/ })
-  perl -pi -0 -e 's,\n( *)([^\n]*supported_cuda_compute_capabilities\s*=\s*\{).*?(\}),\n\1// $ENV{WARNING}\n\1\2$ENV{CUDA_VERSION_OPTS}\3,s' tensorflow/core/common_runtime/gpu/gpu_device.cc
-fi
-
-# Invoke the cuda_config.sh and set up the TensorFlow's canonical view of the Cuda libraries
-(cd third_party/gpus/cuda; ./cuda_config.sh;) || exit -1
+bazel clean --expunge
+bazel fetch //...
 
 echo "Configuration finished"

tensorflow/core/common_runtime/gpu/gpu_device.cc

@@ -785,10 +785,8 @@ struct CudaVersion {
   int minor_part = -1;
 };
 
-// "configure" uses the specific name to substitute the following string.
-// If you change it, make sure you modify "configure" as well.
 std::vector<CudaVersion> supported_cuda_compute_capabilities = {
-    CudaVersion("3.5"), CudaVersion("5.2")};
+    TF_CUDA_CAPABILITIES,};
 
 std::vector<CudaVersion> GetSupportedCudaComputeCapabilities() {
   auto cuda_caps = supported_cuda_compute_capabilities;

tensorflow/core/kernels/lrn_op.cc

@@ -31,7 +31,7 @@ limitations under the License.
 #endif
 
 #if GOOGLE_CUDA
-#include "third_party/gpus/cuda/include/cuda.h"
+#include "cuda/include/cuda.h"
 #include "tensorflow/core/platform/stream_executor.h"
 #include "tensorflow/core/util/stream_executor_util.h"
 #endif  // GOOGLE_CUDA

tensorflow/core/kernels/matmul_op.cc

@@ -25,7 +25,7 @@ limitations under the License.
 #include "tensorflow/core/kernels/fill_functor.h"
 
 #if GOOGLE_CUDA
-#include "third_party/gpus/cuda/include/cuda.h"
+#include "cuda/include/cuda.h"
 #include "tensorflow/core/platform/stream_executor.h"
 #endif  // GOOGLE_CUDA
 

tensorflow/core/ops/ops.pbtxt

@@ -4680,6 +4680,42 @@ op {
   summary: "Decode a PNG-encoded image to a uint8 or uint16 tensor."
   description: "The attr `channels` indicates the desired number of color channels for the\ndecoded image.\n\nAccepted values are:\n\n*   0: Use the number of channels in the PNG-encoded image.\n*   1: output a grayscale image.\n*   3: output an RGB image.\n*   4: output an RGBA image.\n\nIf needed, the PNG-encoded image is transformed to match the requested number\nof color channels."
 }
+op {
+  name: "DecodeGif"
+  input_arg {
+    name: "contents"
+    description: "0-D.  The GIF-encoded image."
+    type: DT_STRING
+  }
+  output_arg {
+    name: "image"
+    description: "3-D with shape `[height, width, channels]`."
+    type_attr: "dtype"
+  }
+  attr {
+    name: "channels"
+    type: "int"
+    default_value {
+      i: 0
+    }
+    description: "Number of color channels for the decoded image."
+  }
+  attr {
+    name: "dtype"
+    type: "type"
+    default_value {
+      type: DT_UINT8
+    }
+    allowed_values {
+      list {
+        type: DT_UINT8
+        type: DT_UINT16
+      }
+    }
+  }
+  summary: "Decode a GIF-encoded image to a uint8 or uint16 tensor."
+  description: "The attr `channels` indicates the desired number of color channels for the\ndecoded image.\n\nAccepted values are:\n\n*   0: Use the number of channels in the GIF-encoded image.\n*   1: output a grayscale image.\n*   3: output an RGB image.\n*   4: output an RGBA image.\n\nIf needed, the GIF-encoded image is transformed to match the requested number\nof color channels."
+}
 op {
   name: "DecodeRaw"
   input_arg {

tensorflow/core/platform/default/build_config/BUILD

@@ -9,7 +9,7 @@ exports_files(["LICENSE"])
 
 load("//tensorflow:tensorflow.bzl", "tf_copts")
 load("//tensorflow:tensorflow.bzl", "tf_cuda_library")
-load("//third_party/gpus/cuda:platform.bzl", "cuda_library_path")
+load("@local_config_cuda//cuda:platform.bzl", "cuda_library_path")
 
 cc_library(
     name = "gtest",
@@ -32,7 +32,7 @@ tf_cuda_library(
     deps = [
         "//tensorflow/stream_executor",
     ] + select({
-        "//third_party/gpus/cuda:darwin": ["IOKit"],
+        "@local_config_cuda//cuda:darwin": ["IOKit"],
         "//conditions:default": [],
     }),
 )
@@ -91,20 +91,20 @@ filegroup(
 cc_library(
     name = "cuda",
     data = [
-        "//third_party/gpus/cuda:{}".format(cuda_library_path("cudart")),
+        "@local_config_cuda//cuda:{}".format(cuda_library_path("cudart")),
     ],
     linkopts = select({
-        "//third_party/gpus/cuda:darwin": [
-            "-Wl,-rpath,third_party/gpus/cuda/lib",
-            "-Wl,-rpath,third_party/gpus/cuda/extras/CUPTI/lib",
+        "@local_config_cuda//cuda:darwin": [
+            "-Wl,-rpath,../local_config_cuda/cuda/lib",
+            "-Wl,-rpath,../local_config_cuda/cuda/extras/CUPTI/lib",
         ],
         "//conditions:default": [
-            "-Wl,-rpath,third_party/gpus/cuda/lib64",
-            "-Wl,-rpath,third_party/gpus/cuda/extras/CUPTI/lib64",
+            "-Wl,-rpath,../local_config_cuda/cuda/lib64",
+            "-Wl,-rpath,../local_config_cuda/cuda/extras/CUPTI/lib64",
         ],
     }),
     deps = [
-        "//third_party/gpus/cuda:cudart",
+        "@local_config_cuda//cuda:cudart",
     ],
 )
 

tensorflow/core/platform/default/gpu/BUILD

@@ -15,9 +15,9 @@ tf_cuda_library(
     copts = tf_copts(),
     cuda_deps = [
         "//tensorflow/core:stream_executor",
-        "//third_party/gpus/cuda:cuda_headers",
-        "//third_party/gpus/cuda:cupti_headers",
+        "@local_config_cuda//cuda:cuda_headers",
+        "@local_config_cuda//cuda:cupti_headers",
     ],
-    data = ["//third_party/gpus/cuda:cupti_dsos"],
+    data = ["@local_config_cuda//cuda:cupti_dsos"],
     visibility = ["//visibility:public"],
 )

tensorflow/core/platform/default/gpu/cupti_wrapper.h

@@ -21,7 +21,7 @@ limitations under the License.
 #include <stddef.h>
 #include <stdint.h>
 
-#include "third_party/gpus/cuda/extras/CUPTI/include/cupti.h"
+#include "cuda/extras/CUPTI/include/cupti.h"
 
 namespace perftools {
 namespace gputools {

tensorflow/core/util/port.cc

@@ -16,7 +16,7 @@ limitations under the License.
 #include "tensorflow/core/util/port.h"
 
 #if GOOGLE_CUDA
-#include "third_party/gpus/cuda/include/cuda.h"
+#include "cuda/include/cuda.h"
 #endif
 
 namespace tensorflow {

tensorflow/g3doc/api_docs/python/functions_and_classes/shard5/tf.train.Optimizer.md

@@ -184,9 +184,8 @@ applies gradients.
 
 ### Gating Gradients
 
-Both `minimize()` and `compute_gradients()` accept a `gate_gradient` argument
-that controls the degree of parallelism during the application of the
-gradients.
+Both `minimize()` and `compute_gradients()` accept a `gate_gradients` argument
+that controls the degree of parallelism during the application of the gradients.
 
 The possible values are: `GATE_NONE`, `GATE_OP`, and `GATE_GRAPH`.
 

tensorflow/g3doc/api_docs/python/train.md

@@ -204,9 +204,8 @@ applies gradients.
 
 ### Gating Gradients
 
-Both `minimize()` and `compute_gradients()` accept a `gate_gradient` argument
-that controls the degree of parallelism during the application of the
-gradients.
+Both `minimize()` and `compute_gradients()` accept a `gate_gradients` argument
+that controls the degree of parallelism during the application of the gradients.
 
 The possible values are: `GATE_NONE`, `GATE_OP`, and `GATE_GRAPH`.
 

tensorflow/g3doc/get_started/os_setup.md

@@ -7,11 +7,10 @@ github source.
 
 The TensorFlow Python API supports Python 2.7 and Python 3.3+.
 
-The GPU version (Linux only) works best with Cuda Toolkit 7.5 and
-cuDNN v4.  other versions are supported (Cuda toolkit >= 7.0 and
-cuDNN 6.5(v2), 7.0(v3), v5) only when installing from sources.
-Please see [Cuda installation](#optional-install-cuda-gpus-on-linux)
-for details.
+The GPU version (Linux & Mac OS X only) works best with Cuda Toolkit 7.5 and
+cuDNN v4. other versions are supported (Cuda toolkit >= 7.0 and cuDNN 6.5(v2),
+7.0(v3), v5) only when installing from sources. Please see [Cuda installation]
+(#optional-install-cuda-gpus-on-linux) for details.
 
 ## Overview
 

tensorflow/python/ops/ctc_ops.py

@@ -48,6 +48,18 @@ def ctc_loss(inputs, labels, sequence_length,
     <= sequence_length(b) for all b.
   ```
 
+  Notes:
+
+  This class performs the softmax operation for you, so inputs should
+  be e.g. linear projections of outputs by an LSTM.
+
+  The `inputs` Tensor's innermost dimension size, `num_classes`, represents
+  `num_labels + 1` classes, where num_labels is the number of true labels, and
+  the largest value `(num_classes - 1)` is reserved for the blank label.
+
+  For example, for a vocabulary containing 3 labels `[a, b, c]`,
+  `num_classes = 4` and the labels indexing is `{a: 0, b: 1, c: 2, blank: 3}`.
+
   Regarding the arguments `preprocess_collapse_repeated` and
   `ctc_merge_repeated`:
 
@@ -84,10 +96,12 @@ def ctc_loss(inputs, labels, sequence_length,
 
   Args:
     inputs: 3-D `float` `Tensor` sized
-      `[max_time x batch_size x num_classes]`.  The logits.
+      `[max_time x batch_size x num_classes]`. The logits.
     labels: An `int32` `SparseTensor`.
       `labels.indices[i, :] == [b, t]` means `labels.values[i]` stores
-      the id for (batch b, time t).  See `core/ops/ctc_ops.cc` for more details.
+      the id for (batch b, time t).
+      `labels.values[i]` must take on values in `[0, num_labels)`.
+      See `core/ops/ctc_ops.cc` for more details.
     sequence_length: 1-D `int32` vector, size `[batch_size]`.
       The sequence lengths.
     preprocess_collapse_repeated: Boolean.  Default: False.

tensorflow/python/ops/variables.py

@@ -1036,8 +1036,7 @@ def report_uninitialized_variables(var_list=None,
 
   Returns:
     A 1-D tensor containing names of the uninitialized variables, or an empty
-    1-D
-    tensor if there are no variables or no uninitialized variables.
+    1-D tensor if there are no variables or no uninitialized variables.
   """
   if var_list is None:
     var_list = all_variables() + local_variables()

tensorflow/python/training/optimizer.py

@@ -89,9 +89,9 @@ class directly, but instead instantiate one of its subclasses such as
 
   ### Gating Gradients
 
-  Both `minimize()` and `compute_gradients()` accept a `gate_gradient` argument
-  that controls the degree of parallelism during the application of the
-  gradients.
+  Both `minimize()` and `compute_gradients()` accept a `gate_gradients`
+  argument that controls the degree of parallelism during the application of
+  the gradients.
 
   The possible values are: `GATE_NONE`, `GATE_OP`, and `GATE_GRAPH`.